Identification of mycoplasm contamination using Raman spectroscopy

ABSTRACT

A manufacturing method comprises collecting a sample from a cell culture used by a manufacturing application, and controlling a Raman spectrometer to collect a Raman spectrum of a targeted volume within the sample. The method further comprises obtaining reference spectra uniquely associated with a known cell line, which comprise at least two of: spectral measurements of mycoplasma by itself, a contaminated cell line, and a pure cell line. Moreover, the method comprises comparing the reference spectra to the collected spectrum, and identifying whether there is at least one unnatural molecular composition within the collected spectrum based upon the comparison of the reference spectra to the collected spectrum. An indication is provided as to whether mycoplasma is detected in the collected Raman spectrum where at least one unnatural molecular composition is identified within the collected spectrum, and the manufacturing application is stopped where mycoplasma is detected in the collected Raman spectrum.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/191,887, filed Feb. 27, 2014, entitled “IDENTIFICATION OF MYCOPLASMCONTAMINATION IN BIOTECHNOLOGY PRODUCTION USING RAMAN SPECTROSCOPY”, nowallowed, which is a bypass continuation of International Application No.PCT/US2012/052777, filed Aug. 29, 2012, entitled “IDENTIFICATION OFMYCOPLASM CONTAMINATION IN BIOTECHNOLOGY PRODUCTION USING RAMANSPECTROSCOPY”, which claims the benefit of U.S. Provisional PatentApplication Ser. No. 61/528,849, filed Aug. 30, 2011, entitled“IDENTIFICATION OF MYCOPLASM CONTAMINATION IN BIOTECHNOLOGY PRODUCTIONUSING RAMAN SPECTROSCOPY”, the disclosures of which are herebyincorporated by reference.

BACKGROUND

The present disclosure relates to the detection of mycoplasmas, and moreparticularly to the utilization of Raman Spectroscopy to distinguishand/or otherwise identify unmycoplasma contaminated cells frommycoplasma contaminated cells in biotechnology production.

Numerous modern bioprocess manufacturing applications utilize cellculture systems. For example, in a conventional bioprocess, a cellculture may be used to catalyze biochemical reactions withinmicroorganisms to generate cellular components thereof. After a seriesof reactions that are contained in a controlled environment, the cellculture chemically changes reactants into end products.

Unfortunately, mycoplasma contamination of cell culture systems isdetrimental to such bioprocess manufacturing applications. Mycoplasmaslack a cell wall. Instead, mycoplasma rely upon hosts to maintain theirplasma membrane. In this regard, mycoplasmas bind with cell walls oftheir hosts to obtain nutrients. As such, mycoplasma is extremely smalland difficult to detect and filter. Moreover, mycoplasma can causeunexpected deviations in the host cell, e.g., in cell growth,metabolism, function, synthesis, etc. As a result, the cell culture maybecome contaminated, thus skewing the manufacturing of products from thecell culture and likely destroying the utility of the cell culture.

BRIEF SUMMARY

According to aspects of the present disclosure, a manufacturing methodcomprises collecting a sample from a cell culture used by amanufacturing application. The method also comprises controlling a Ramanspectrometer, by a processor, to collect a Raman spectrum of a targetedvolume within the sample so as to collect a Raman spectrum of a singlecell of a known cell line of interest. The method further comprisesobtaining reference spectra uniquely associated with the known cellline. The reference spectra comprise at least two of spectralmeasurements of mycoplasma by itself, a contaminated cell line, and apure cell line. Moreover, the method comprises comparing, using aprocessing device, the reference spectra to the collected spectrum, andidentifying whether there is at least one unnatural molecularcomposition within the collected spectrum based upon the comparison ofthe reference spectra to the collected spectrum. In this regard, themethod yet further comprises providing an indication as to whethermycoplasma is detected in the collected Raman spectrum where at leastone unnatural molecular composition is identified within the collectedspectrum, and stopping the manufacturing application where mycoplasma isdetected in the collected Raman spectrum.

For example, the targeted volume may be identified as a potential hostvolume if the targeted volume is identified as a belonging to a knownline, such as Chinese hamster ovarian line or Escherichia coli line. Inthis regard, comparing the reference spectrum to the collected spectrummay comprise computing by the processing device, a difference spectrumas the difference between the reference spectrum, such as the spectrumof a Chinese hamster ovarian line or Escherichia coli line, and thecollected spectrum. Moreover, the collected Raman spectrum may bemeasured so as to contain sufficient spectral content to examine atleast substantially the entirety of the contents of the targeted volume,e.g., a single cell.

According to further aspects of the present disclosure, a system thatdetects mycoplasma in a manufacturing application, comprises an opticalimaging system and a processor. The optical imaging system implements aRaman spectrometer that is controlled to direct a laser to a targetedvolume within a sample area so as to collect a Raman spectrum of asingle cell of a known cell line of interest. The processor is coupledto the optical imaging system. In this manner, the processor executesprogram code to receive the Raman spectrum, and to access referencespectra that describes the known line. The reference spectra comprise atleast two of: spectral measurements of mycoplasma by itself, acontaminated cell line, and a pure cell line. The processor furtherexecutes program code to compare the reference spectra to the collectedspectrum, and identify whether there is at least one unnatural molecularcomposition within the collected spectrum based upon the comparison ofthe reference spectra to the collected spectrum. Yet further, theprocessor executes program code to provide an indication as to whethermycoplasma is detected in the collected Raman spectrum based uponwhether at least one unnatural molecular composition is identifiedwithin the collected spectrum, and stop the manufacturing applicationwhere mycoplasma is detected in the collected Raman spectrum.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a simplified illustration of a Raman spectroscopy system,according to various aspects of the present disclosure;

FIG. 2 is a block diagram of a processing device that processes Ramanspectral data, e.g., which may be collected from the Raman system ofFIG. 1;

FIG. 3 is a block diagram of a method of detecting mycoplasma accordingto various aspects of the present disclosure; and

FIG. 4 is a chart illustrating exemplary spectra showing mycoplasmadetection of an illustrative sample, according to various aspects of thepresent disclosure.

DETAILED DESCRIPTION

Many bioprocesses utilize cell cultures. For instance, a bioprocess mayutilize hosts cells for the industrial production of recombinant proteinpharmaceuticals. By way of illustration, biotechnology in pharmaceuticalmanufacturing use recombinant technology to modify materials withinbacteria, such as Escherichia coli (E. coli), to produce human insulin.Further, a wide variety of other cell lines are used to contain andserve as a template for the biosynthesis of many new drugs. However,when the cell lines become contaminated, the recombinant process doesnot yield the correct therapeutic material or drug.

Mycoplasma is a common and difficult to diagnose contaminant of suchbioprocess manufacturing applications. For instance, mycoplasmas cancontaminate and destroy cell cultures used to catalyze biochemicalreactions within microorganisms. Moreover, mycoplasma can persist forlong periods of time without apparent cell damage, which can causechallenges in the early detection of the mycoplasma contamination. Assuch, mycoplasmas are particularly detrimental to industrialbioprocesses, including bioprocesses that utilize host cells forindustrial production of recombinant protein pharmaceuticals.

Mycoplasmas do not have cell walls of their own and rely on anassociation with a host cell to survive. Because mycoplasma exist withinanother cell, it is difficult to detect the contaminant, even withchemical methods such as ELISA (an antigen-based enzyme-linkedimmunosorbent assay) or antibody-antigen detection systems.

In addition to Escherichia coli, another susceptible cell line tomycoplasma contamination is Chinese hamster ovarian (CHO) cells, whichare widely used in bioprocessing to produce complicated proteinaceousdrugs. The host CHO cells express recombinant proteins very efficientlyand have become the mammalian analog to Escherichia coli in thebiotechnology industry. When the CHO cells express optimally, they yieldvery high levels of proteins needed for drug manufacturing.

According to aspects of the present disclosure, Raman spectroscopy isutilized to distinguish and/or otherwise identify host cells that arefree from mycoplasma contamination (unmycoplasma contaminated hostcells) from mycoplasma contaminated cells in a biotechnology productionor research application. Detection of mycoplasma enables processes to bestopped if tested samples indicate that a product is contaminated,saving potentially weeks of process time and expensive reagents.

Detection of mycoplasma in a cell culture can be accomplished accordingto various aspects of the present disclosure, using an optical imagingsystem that implements a Raman spectrometer. More particularly, anoptical imaging system implements a Raman spectrometer that iscontrolled by a processor to direct a laser to a targeted volume withina sample area so as to collect a Raman spectrum of a single cell of aknown cell line of interest, as will be described in greater detailherein.

Referring now to the drawings, and in particular, to FIG. 1, asimplified Raman system is provided for purposes of clear illustrationherein. The Raman system includes an optical imaging system 10 having ingeneral, a light source 12, optics 14 and at least one image outputdevice 16. The light source 12 in the illustrative example comprises ahigh intensity laser capable of generating a laser beam 18 having anarrow spectral bandwidth. The optics 14 comprise one or more opticalcomponents, such as lenses, reflection surfaces, and/or other opticaldevices necessary to direct the laser beam 18 towards a sample area 20.For instance, as illustrated, the laser beam 18 passes through firstoptics 22, e.g., one or more optional lenses and/or reflection surfaces,which direct the laser beam 18 towards an optical device 24 such as along pass dichroic mirror. As illustrated, the laser beam 18 travelsalong a first optical path as schematically represented by a solid arrowpassing through the optics 22.

Light from the laser beam 18 is reflected by the optical device 24 alonga second optical path so as to pass the laser beam 18 through anobjective 26 as schematically illustrated by the solid arrow pointingfrom the optical device 24 towards the objective 26. The objective 26serves to focus the laser beam 18 onto the sample within the sample area20. For instance, according to various aspects of the presentdisclosure, the objective 26 may be utilized focus the laser beam 18onto a single cell located within the sample area 20, as will bedescribed in greater detail herein.

According to various aspects of the present disclosure, the sample area20 includes a sample collected or otherwise deposited, e.g., from a cellculture, onto an interrogation region 20A, e.g., a sample substratewithin the sample area. However, any desired sampling and/or samplepreparation techniques may be utilized to collect a suitable sample forinterrogation. Regardless of sampling technology, a targeted volume ofthe sample collected in the interrogation region 20A of the sample area20 is illuminated by the light source 12.

Scattered and dispersed light is collected from the sample area 20 backthrough the objective 26 along a third optical path that is generallyopposite in direction of the second optical path. In this regard, theinteraction between the laser light and the sample collected in thesample area 20 leads to Raman scattering of light that is shifted inwavelength from the light source 12. As such, the light directed alongthe third optical path includes inelastically scattered photons due toRaman scattering. The inelastically scattered photons are schematicallyillustrated along the third optical path by the dash dot arrow pointingfrom the objective 26 towards the optical device 24 to distinguish theRaman scattering from the light (solid arrow pointing from the objective26 towards the optical device 24) at the wavelength of the laser.

The light along the third optical path is directed by the optical device24 along a fourth optical path, which is parallel to the third opticalpath and is seen between the optical device 24 and a filter device 28.In a manner analogous to that set out above, the inelastically scatteredphotons are schematically illustrated along the fourth optical path bythe dash dot arrow to distinguish the Raman scattering from the light(solid arrow) at the wavelength of the laser.

The inelastically scattered photons directed along the fourth opticalpath are separated from the elastic incident photons, e.g., using atleast one appropriate filter device 28, e.g., a longpass filter, abandpass filter, etc., such that the inelastically scattered photons arepassed to a spectrometer 30 and a processing device 32, which implementsone or more filters as described in greater detail herein. As such, onlythe dash dot arrow corresponding to the inelastically scattered photons(and not the solid arrow corresponding to light at the wavelength of thelaser) is schematically illustrated as passing from the filter device 28to the spectrometer 30.

In a non-limiting but illustrative implementation, the spectrometer 30may include a spectrometer grating that passes the filtered light to theimage output device 16, e.g., a two dimensional charge coupled device(CCD) where the divergence in angles of the light exiting the gratingcauses light at different wavelengths to arrive on different pixels ofthe CCD to capture spectral data representative of the Raman spectra ofthe particle under interrogation. Thus, the image output device 16receives inelastically scattered photons to output information regardingthe sample interrogated on the sample substrate.

The Raman spectrum collected from the CCD of the optical output device16 is collected by the processing device 32 and an analysis engine 36 ofthe processing device 32 analyzes the collected spectrum to determinewhether the collected spectrum suggests that mycoplasma is present inthe tested sample.

According to aspects of the present disclosure, the processor isconfigured to receive the Raman spectrum. The processor is furtherconfigured to access a reference spectrum, where the reference spectrumdescribes a known line of interest via a spectrum that is known to befree of mycoplasma. The processor is still further configured to comparethe reference spectrum to the collected spectrum, identify whether thereare unnatural molecular compositions within the collected spectrum basedupon the comparison of the reference spectrum to the collected spectrumand provide an indication as to whether mycoplasma is detected in thecollected spectrum based upon whether unnatural molecular compositionsare identified within the collected spectrum.

In an illustrative implementation, the optical imaging system iscontrolled by the processor to scan the sample area to locate targetedvolumes that are suspected of containing a cell of the known cell lineof interest. For example, the processor identifies whether the targetedvolume contains a cell from a select one of a Chinese hamster ovarianline and Escherichia coli line.

As an illustrative example of the above implementation, the processingdevice 32 directs the laser source 12 to emit a beam 18 that is focusedby the objective 26 onto a single cell within the interrogation region20A of the sample area 20. The processing device 32 then interrogatesthe sample area at the determined target location to produceinterrogation data used by the analysis engine to determine whether thetargeted and interrogated cell exhibits characteristics of mycoplasmacontamination, as described more fully herein.

In a further illustrative exemplary implementation, the processor of theprocessing device 32 broadly interrogates the interrogation region 20Aof the sample area 20. The processing device then selects from withinthe interrogated region, one or more specific cells to target for moredetailed interrogation. The processing device 32 then directs the lasersource 12 to emit a beam 18 that is focused by the objective 26 onto asingle selected and targeted cell within the interrogation region 20A ofthe sample area 20. The processing device 32 then interrogates thesample area at the determined target location to produce interrogationdata.

The analysis engine 36 evaluates the specific targeted spectrum todetermine whether the targeted and interrogated cell exhibitscharacteristics of mycoplasma contamination. For instance, in anillustrative implementation, the processor compares the referencespectrum to the collected spectrum by computing a difference spectrum asthe difference between the reference spectrum and the collectedspectrum. The processor further identifies whether there are unnaturalmolecular compositions within the collected spectrum based upon thecomparison of the reference spectrum to the collected spectrum byidentifying unnatural molecules based upon an analysis of the differencespectrum. The processing device 32 can optionally trigger an event suchas an alarm or message if mycoplasma is detected.

In this regard, other optics configurations may be implemented withinthe spirit and scope of the present disclosure. For instance, the optics14 may utilize various combinations of filters, beam splitters, lenses,mirrors etc. Likewise, the optical output device 16 can be implementedin alternative configurations that are suitable for Raman processing.Moreover, the processing device 32 may utilize a first optical devicefor general interrogation, and a second optical device for targeting aspecific cell within the sample area, etc. Still further, othertargeting and/or selection approaches can be utilized to identify theregion of the sample area 20 for Raman analysis.

In addition, Raman spectroscopy can be applied using any of the systemsand/or processes set out in U.S. Pat. No. 7,532,314, issued May 12, 2009to Black et al., entitled “Systems and Methods for Biological andChemical Detection”, the disclosure of which is hereby incorporated byreference in its entirety.

Referring to FIG. 2, a block diagram of an exemplary implementation ofthe processing device 32 is depicted in accordance with various aspectsof the present disclosure. The processing device 32 comprises one ormore processors 42 connected to system bus 44. Also connected to systembus 44 is memory 48, a computer usable storage medium 48 and one or moreinput/output devices 50. The computer usable storage medium 48 hascomputer usable program code embodied thereon, which is executed by theprocessor 42 to implement any aspect of the present disclosure, forexample, to implement the analysis engine 36 and/or any aspect of any ofthe mycoplasma detection methods described and set out more fullyherein.

The architecture and features of the processing device 32 are presentedby way of illustration and not by way of limitation. In that regard, theprocessor 32 may have an alternative architecture and/or features tothat described with reference to FIG. 2. Moreover, the processing device32 need not be physically linked to the optical device 16. Rather, theoptical imaging system 10 could collect data that is stored forsubsequent processing by the processing device 32, whether integratedwith the optical imaging system 10, located off-line, off-site orotherwise, so long as the processing device 32 can implement the filtersas described more fully herein.

Recombinant technology can be used to modify materials within bacteria.In this regard, a wide variety of cell lines are used to contain andserve as a template for the biosynthesis of many products. However, whenthe cell lines become contaminated, the recombinant process does notyield the correct therapeutic material or drug. However, according toaspects of the present disclosure, methods are provided to identifyunmycoplasma contaminated host cells from uncontaminated cells.

Referring to FIG. 3, a method 60 is provided for detecting mycoplasma ina sample. The method comprises collecting a Raman spectrum of a targetedvolume within a sample at 62, where the targeted volume contains a knowncell line of interest. For instance, the targeted volume may comprise acell located within an interrogation region 20A of the sample area 20 inthe optical imaging system 10 of FIG. 1. By way of illustration, themethod 60 may be utilized to inspect a culture in a bioprocess thatcontains a susceptible cell line such as the Chinese hamster ovarianline of cells or the Escherichia coli line of cells. Regardless, thecollected Raman spectrum preferably targets a single cell of thecorresponding known cell line.

The method further comprises obtaining a reference spectrum uniquelyassociated with the known cell line at 64 where the obtained referencespectrum is known to be free of mycoplasma contamination. In anillustrative example, the collection of the known spectrum consists ofthe spectral measurements of mycoplasma by itself, a contaminated cellline and a pure cell line.

The Raman system used to collect the spectrum may be required to scanthe sample of interest to identify at least one targeted volume as apotential host for mycoplasma where the targeted volume is identified asa belonging to a known line of interest. The Raman system mayalternatively otherwise evaluate regions of the overall sample area tolocate and identify a targeted volume that contains a cell from the cellline of interest. As such, the method may perform the collecting of aRaman spectrum of a targeted volume within a sample of interest andidentifying the targeted volume as a potential host for mycoplasma ifthe targeted volume is identified as a belonging to a known line, e.g.,Chinese hamster ovarian line of cells or the Escherichia coli line ofcells, by way of example.

The method still further comprises comparing the reference spectrum 64to the collected spectrum at 66. In an exemplary implementation, thereference spectrum is compared to the collected spectrum using theprocessing device 32, and more particularly, the analysis engine 36 ofFIG. 1. Particularly, the reference spectrum is compared to thecollected spectrum by computing, e.g., by the processing device 32and/or analysis engine 36, a difference spectrum as the differencebetween the reference spectrum and the collected spectrum.

The method also comprises identifying whether there are unknown orunnatural molecular compositions within the collected spectrum basedupon the comparison of the reference spectrum to the collected spectrumat 68 and providing an indication as to whether mycoplasma is detectedin the collected Raman spectrum based upon whether unnatural molecularcompositions are identified within the collected spectrum at 70. In thisregard, Raman spectroscopy is utilized to identify unmycoplasmacontaminated host cells from mycoplasma contaminated cells. As a result,contaminated processes can be stopped, thus saving potentially, weeks ofprocess time.

In an exemplary implementation, an indication as to whether mycoplasmais detected in the collected Raman spectrum is based upon whetherunnatural molecular compositions are identified within the collectedspectrum. Unnatural molecular compositions can be identified byidentifying unnatural molecules based upon an analysis of a differencespectrum computed between the collected spectrum and the referencespectrum.

According to various aspects of the present disclosure, Ramanspectroscopy has been developed and used to identify bacteria. Theidentification is phenomenological and yields a very complex spectralprofile that is indicative of the proteinaceous composition of the cell.In this regard, spectral differences exist between cells that are knownto be pure and contaminated cells. However, by evaluating a sample,e.g., using the system of FIG. 1 and/or the method of FIG. 3, the earlydetection of contaminated cell lines can be achieved, thus potentiallysaving weeks of bioprocess time and money.

According to aspects of the present disclosure, the entire contents of acell are examined. If a parasitic cell exists, e.g., within a Chinesehamster ovarian host cell or Escherichia coli host cell in the examplesprovided herein, the Raman spectrum looks uniquely different from anon-contaminated cell. Thus, Raman spectroscopy as set out and describedmore fully herein provides an early diagnostic technique forbiotechnology process monitoring.

Referring to FIG. 4, a sample spectrum is shown. As illustrated, thewavenumber is plotted on the axis of abscissa and Raman intensity isplotted on the axis of the ordinate. A difference measure is plotted onan axis opposite of the Raman intensity. As illustrated in FIG. 4,subtle differences between contaminated and uncontaminated cells aredetermined. In this regard, the measured spectral information isdescribed as a superposition of all the molecular material detected,e.g., all molecular material illuminated by the laser beam 18 of thelaser source 12 in FIG. 1.

In an illustrative bioprocess application, a Chinese ovarian hamstercell is evaluated. The collected spectral information is illustratedwith the trace having dots spaced throughout the trace. A knownuncontaminated trace, represented by a solid, light gray trace isoverlaid with the collected spectrum. The identity of the cultured cellline is known, e.g., the Raman spectral signature of a Chinese hamsterovarian host cell is known or has otherwise been previously determined.Thus, according to various aspects of the present disclosure, adifference spectrum (known spectrum—measured spectrum) illustrates thatthere are unknown or unnatural molecular compositions within theilluminated volume (cell). The difference spectrum is illustrated as thelight solid trace on showing the scale on the right most axis of theordinate. Notably, if the collected spectrum matched the known spectrum,the difference spectrum would be a substantially horizontal line.However, differences at various spectral positions indicate unnaturalmolecular compositions within the collected sample. By evaluating thisdifference signal, information contained therein serves as an indicationof whether mycoplasma is present in the sample.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the disclosure.As used herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The description of the present disclosure has been presented forpurposes of illustration and description, but is not intended to beexhaustive or limited to the disclosure in the form disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of thedisclosure.

Having thus described the disclosure of the present application indetail and by reference to embodiments thereof, it will be apparent thatmodifications and variations are possible without departing from thescope of the disclosure defined in the appended claims.

What is claimed is:
 1. A method of detecting mycoplasma in amanufacturing application, comprising: collecting a sample from a cellculture used by a manufacturing application; controlling an opticalimaging system implementing a Raman spectrometer to direct a laser to atargeted volume within a sample area so as to collect a Raman spectrumof a single cell of a known cell line of interest; receiving, by aprocessor, the Raman spectrum; accessing reference spectra uniquelyassociated with the known cell line and which describes the known line,the reference spectra comprising at least one of: spectral measurementsof mycoplasma by itself, and a contaminated cell line; comparing, usingthe processor, the reference spectra to the collected spectrum bycomputing a difference spectrum from the collected spectrum and a selectspectrum of the reference spectra; identifying whether there is at leastone unnatural molecular composition within the collected spectrum basedupon the comparison of the reference spectra to the collected spectrumby evaluating differences at select spectral positions of the differencespectrum that indicate unnatural molecular compositions; providing anindication as to whether mycoplasma is detected in the collected Ramanspectrum where at least one unnatural molecular composition isidentified within the collected spectrum; and stopping the manufacturingapplication where mycoplasma is detected in the collected Ramanspectrum.
 2. The method according to claim 1, wherein: accessingreference spectra uniquely associated with the known cell line,comprises obtaining the reference spectra comprising all three ofspectral measurements of mycoplasma by itself, a contaminated cell line,and a pure cell line.
 3. The method according to claim 1, wherein:stopping the manufacturing application comprises triggering an eventincluding at least one of sounding an alarm and sending a message. 4.The method according to claim 1, wherein: collecting a sample from acell culture used by a manufacturing application comprises collectingthe sample from a cell culture used by a bioprocess manufacturingapplication that uses recombinant technology to modify materials withinbacteria.
 5. The method according to claim 1, wherein: controlling anoptical imaging system implementing a Raman spectrometer to direct alaser to a targeted volume within a sample area so as to collect a Ramanspectrum of a single cell of a known cell line of interest furthercomprises: utilizing a first optical device for general interrogation,and a second optical device for targeting a specific cell within thesample area.
 6. The method according to claim 1, further comprising:identifying whether the targeted volume contains a cell from a selectone of a Chinese hamster ovarian line and Escherichia coli line.
 7. Themethod according to claim 1, wherein the targeted volume comprises asingle cell.
 8. The method according to claim 7, wherein the collectedRaman spectrum contains sufficient spectral content to examine at leastsubstantially the entirety of the contents of the cell within thetargeted volume.
 9. The method according to claim 1, wherein thecollected Raman spectrum is a superposition of all the molecularmaterial of a single cell being illuminated by a laser used to collectthe Raman spectrum.
 10. The method according to claim 1, furthercomprising: scanning the sample of interest to identify at least onetargeted volume as a potential host for mycoplasma where the targetedvolume is identified as a belonging to a known line of interest; andevaluating at least one targeted volume determined to be a potentialhost for mycoplasma by: collecting a Raman spectrum of the targetedvolume within a sample under evaluation, the targeted volume containinga known cell line of interest; comparing, using a processing device, thereference spectra to the collected Raman spectrum; identifying whetherthere is at least one unnatural molecular composition within thecollected spectrum based upon the comparison of the reference spectra tothe collected spectrum; and providing an indication as to whethermycoplasma is detected in the collected Raman spectrum based uponwhether unnatural molecular compositions are identified within thecollected spectrum.
 11. The method according to claim 1, whereincomputing a difference spectrum comprises computing a differencespectrum from the collected spectrum and the contaminated cell linespectrum from the reference spectra.
 12. The method according to claim1, wherein computing a difference spectrum comprises computing adifference spectrum from the collected spectrum and the mycoplasma byitself spectrum from the reference spectra.
 13. A system that detectsmycoplasma in a manufacturing application, comprising: an opticalimaging system implementing a Raman spectrometer that is controlled todirect a laser to a targeted volume within a sample area so as tocollect a Raman spectrum of a single cell of a known cell line ofinterest; a processor coupled to the optical imaging system, wherein theprocessor executes program code to: receive the Raman spectrum, theprocessor further configured to access reference spectra that describesthe known line, the reference spectra comprising all three of spectralmeasurements of mycoplasma by itself, a contaminated cell line, and apure cell line; compare the reference spectra to the collected spectrumby computing a difference spectrum from the collected spectrum and aselect spectrum of the reference spectra; identify whether there is atleast one unnatural molecular composition within the collected spectrumbased upon the comparison of the reference spectra to the collectedspectrum by evaluating differences at select spectral positions of thedifference spectrum that indicate unnatural molecular compositions;provide an indication as to whether mycoplasma is detected in thecollected Raman spectrum based upon whether at least one unnaturalmolecular composition is identified within the collected spectrum; andstop the manufacturing application where mycoplasma is detected in thecollected Raman spectrum.
 14. The system according to claim 13, wherein:the optical imaging system is controlled by the processor to scan thesample area to locate targeted volumes that are suspected of containinga cell of the known cell line of interest.
 15. The system according toclaim 13, wherein the processor is further configured to: identifywhether the targeted volume contains a cell from a select one of aChinese hamster ovarian line and Escherichia coli line.
 16. The systemaccording to claim 13, wherein: the processor further executes programcode to stop the bioprocess by triggering an event including at leastone of sounding an alarm and sending a message.
 17. The system accordingto claim 13, wherein: the processor further executes program code tocontrol a Raman spectrometer to collect a Raman spectrum of a targetedvolume within the sample by: utilizing a first optical device forgeneral interrogation, and a second optical device for targeting aspecific cell within the sample area.
 18. The system according to claim13, wherein the program code for computing a difference spectrumcomprises program code for computing a difference spectrum from thecollected spectrum and the contaminated cell line spectrum from thereference spectra.
 19. The system according to claim 13, wherein theprogram code for computing a difference spectrum comprises program codefor computing a difference spectrum from the collected spectrum and themycoplasma by itself spectrum from the reference spectra.